==================== Environment Info ====================
Dataset Path: /workspace/data
===========================================================

 Dataset found, listing contents:
total 12
drwxr-sr-x. 3 1000960000 1000520000 4096 Nov  3 07:11 .
drwxrwsrwx. 4         99 1000520000 4096 Nov  3 07:11 ..
drwxr-sr-x. 3 1000960000 1000520000 4096 Nov  3 07:11 FashionMNIST

 Using dependencies from shared volume: /workspace/lib

==================== Starting Distributed Training ====================
W1103 07:11:57.763000 3 torch/distributed/run.py:874] 
W1103 07:11:57.763000 3 torch/distributed/run.py:874] *****************************************
W1103 07:11:57.763000 3 torch/distributed/run.py:874] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W1103 07:11:57.763000 3 torch/distributed/run.py:874] *****************************************
2026-11-03T07:12:02Z INFO     Distributed Training with WORLD_SIZE: 4, RANK: 0, LOCAL_RANK: 0.
2026-11-03T07:12:02Z INFO     Distributed Training with WORLD_SIZE: 4, RANK: 1, LOCAL_RANK: 1.
2026-11-03T07:12:02Z INFO     [CPU0] Epoch 0 | Batchsize: 64 | Steps: 235 | World Size: 4
2026-11-03T07:12:02Z INFO     [CPU1] Epoch 0 | Batchsize: 64 | Steps: 235 | World Size: 4
2026-11-03T07:12:02Z INFO     Train Epoch: 0 [0/60000 (0%)]	Loss: 2.302490
2026-11-03T07:12:03Z INFO     Train Epoch: 0 [2560/60000 (4%)]	Loss: 4.846509
2026-11-03T07:12:04Z INFO     Train Epoch: 0 [5120/60000 (9%)]	Loss: 1.457924
2026-11-03T07:12:06Z INFO     Train Epoch: 0 [7680/60000 (13%)]	Loss: 0.972700
2026-11-03T07:12:07Z INFO     Train Epoch: 0 [10240/60000 (17%)]	Loss: 0.586782
2026-11-03T07:12:08Z INFO     Train Epoch: 0 [12800/60000 (21%)]	Loss: 0.491186
2026-11-03T07:12:09Z INFO     Train Epoch: 0 [15360/60000 (26%)]	Loss: 0.419014
2026-11-03T07:12:10Z INFO     Train Epoch: 0 [17920/60000 (30%)]	Loss: 0.566003
2026-11-03T07:12:11Z INFO     Train Epoch: 0 [20480/60000 (34%)]	Loss: 0.582969
2026-11-03T07:12:13Z INFO     Train Epoch: 0 [23040/60000 (38%)]	Loss: 0.505342
2026-11-03T07:12:14Z INFO     Train Epoch: 0 [25600/60000 (43%)]	Loss: 0.380089
2026-11-03T07:12:15Z INFO     Train Epoch: 0 [28160/60000 (47%)]	Loss: 0.438308
2026-11-03T07:12:16Z INFO     Train Epoch: 0 [30720/60000 (51%)]	Loss: 0.362644
2026-11-03T07:12:17Z INFO     Train Epoch: 0 [33280/60000 (55%)]	Loss: 0.286582
2026-11-03T07:12:18Z INFO     Train Epoch: 0 [35840/60000 (60%)]	Loss: 0.735832
2026-11-03T07:12:20Z INFO     Train Epoch: 0 [38400/60000 (64%)]	Loss: 0.662185
2026-11-03T07:12:21Z INFO     Train Epoch: 0 [40960/60000 (68%)]	Loss: 0.304395
2026-11-03T07:12:22Z INFO     Train Epoch: 0 [43520/60000 (72%)]	Loss: 0.391899
2026-11-03T07:12:23Z INFO     Train Epoch: 0 [46080/60000 (77%)]	Loss: 0.599032
2026-11-03T07:12:24Z INFO     Train Epoch: 0 [48640/60000 (81%)]	Loss: 0.429187
2026-11-03T07:12:26Z INFO     Train Epoch: 0 [51200/60000 (85%)]	Loss: 0.429314
2026-11-03T07:12:27Z INFO     Train Epoch: 0 [53760/60000 (89%)]	Loss: 0.455180
2026-11-03T07:12:28Z INFO     Train Epoch: 0 [56320/60000 (94%)]	Loss: 0.538068
2026-11-03T07:12:29Z INFO     Train Epoch: 0 [58880/60000 (98%)]	Loss: 0.173033
2026-11-03T07:12:30Z INFO     [CPU1] Epoch 0 completed | Avg Loss: 0.640963 | Batches: 235
2026-11-03T07:12:30Z INFO     [CPU0] Epoch 0 completed | Avg Loss: 0.659404 | Batches: 235
2026-11-03T07:12:30Z INFO     [CPU1] Training is finished
2026-11-03T07:12:30Z INFO     [CPU0] Training is finished

==================== Training Complete ====================